SAS®
FOR REAL WORLD EVIDENCE

End-to-end capabilities for gleaning new scientific and commercial insights from real-world evidence – from data management, to cohort extraction, to advanced analytics and more – powered by SAS Health Analytics Framework.

Data integration and management

Brings together any and all real-world data sources in a single platform. Automatically maps data to a common data model, and refreshes cohorts and outputs as new data arrives.

Generates insights from real-world data to support decisions on treatment regimens, gaps in care, reimbursement, formulary access or clinical development.

Massive, scalable computing power

A point-and-click interface lets you explore massive data sources with little or no lag time. Grid computing runs calculations on millions of rows of data in seconds rather than minutes, hours or days.

Flexible deployment options

Runs on commodity hardware, in a private or public cloud infrastructure, Cloud Foundry platform as a service (PaaS) or managed software as a service (SaaS).

Achieve faster time to insight and gain a competitive advantage.

Gather relevant real-world data from a variety of sources.

Easily integrate real-world data from internal and third-party sources – point-of-care systems, electronic medical records, insurance claims, patient-reported outcomes, third-party data providers and more. An automated process cleanses and prepares the data, and maps it to a common data model for side-by-side comparison. You spend less time preparing data and more time learning from it.

Even nontechnical users can navigate, visualize and explore huge amounts of data quickly with an easy-to-use, point-and-click interface to powerful, in-memory analytics. A library of prebuilt analytical models infused with innovative algorithms provides access to a wide range of analytic tools – from simple descriptive statistics, to predictive analytics, to machine learning methods. You can also create meaningful reports and share them via mobile devices to support decisions on brand strategy, treatment regimens, pricing, reimbursement, formulary access and more.

Visualize and analyze cohort data.

An interactive drag-and-drop cohort builder supports complex cohort queries with temporal relationships – no coding required. You can easily explore cohort characteristics and the effect of inclusion/exclusion criteria on patient populations to deter­mine study feasibility. Cohort definitions can be saved for reuse, modified and applied to other real-world data assets for comparisons across populations, saving time and resources. You can also validate results and do further analysis using in-memory analysis and visualization in SAS or other technologies (e.g., R, Python and third-party visualization tools).

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Learn how to establish a technology foundation for creating real-world evidence.